Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLingfei Wu
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j20]Xiaojie Guo
, Shugen Wang, Hanqing Zhao, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Jianchao Lu, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Intelligent online selling point extraction and generation for e-commerce recommendation. AI Mag. 44(1): 16-29 (2023)- [j19]Yanyan Zou, Xueying Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Mian Ma, Sulong Xu, Han Yu, Lingfei Wu:
Automatic product copywriting for e-commerce. AI Mag. 44(1): 41-53 (2023) - [j18]Xiang Ling, Lingfei Wu, Jiangyu Zhang, Zhenqing Qu, Wei Deng, Xiang Chen, Yaguan Qian, Chunming Wu, Shouling Ji, Tianyue Luo, Jingzheng Wu, Yanjun Wu:
Adversarial attacks against Windows PE malware detection: A survey of the state-of-the-art. Comput. Secur. 128: 103134 (2023) - [j17]Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long:
Graph Neural Networks for Natural Language Processing: A Survey. Found. Trends Mach. Learn. 16(2): 119-328 (2023) - [j16]Yuyang Gao, Tanmoy Chowdhury, Lingfei Wu, Liang Zhao:
Modeling Health Stage Development of Patients With Dynamic Attributed Graphs in Online Health Communities. IEEE Trans. Knowl. Data Eng. 35(2): 1831-1843 (2023) - [j15]Xiang Ling, Lingfei Wu, Saizhuo Wang, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, Shouling Ji:
Multilevel Graph Matching Networks for Deep Graph Similarity Learning. IEEE Trans. Neural Networks Learn. Syst. 34(2): 799-813 (2023) - [c91]Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu:
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation. AAAI 2023: 4339-4346 - [c90]Dongjie Wang, Lingfei Wu, Denghui Zhang, Jingbo Zhou, Leilei Sun, Yanjie Fu:
Human-Instructed Deep Hierarchical Generative Learning for Automated Urban Planning. AAAI 2023: 4660-4667 - [c89]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
SkillQG: Learning to Generate Question for Reading Comprehension Assessment. ACL (Findings) 2023: 13833-13850 - [c88]Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo:
Graph Neural Networks: Foundation, Frontiers and Applications. KDD 2023: 5831-5832 - [c87]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2023). KDD 2023: 5891-5892 - [c86]Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang:
RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2023: 5901-5902 - [c85]Zhendong Chu, Hongning Wang, Yun Xiao, Bo Long, Lingfei Wu:
Meta Policy Learning for Cold-Start Conversational Recommendation. WSDM 2023: 222-230 - [c84]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [c83]Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu:
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks. WWW 2023: 727-736 - [c82]Vachik S. Dave, Linsey Pang, Xiquan Cui, Lingfei Wu, Hamed Zamani, George Karypis:
The 2nd Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom). WWW (Companion Volume) 2023: 850-853 - [i113]Hongru Yang, Yingbin Liang, Xiaojie Guo, Lingfei Wu, Zhangyang Wang:
Pruning Before Training May Improve Generalization, Provably. CoRR abs/2301.00335 (2023) - [i112]Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu:
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks. CoRR abs/2302.11396 (2023) - [i111]Zak Risha, Yiling Lin, Erin Leahey, Lingfei Wu:
Replacing the Renaissance Man: Are Teams More than the Sum of Their Parts? CoRR abs/2304.14518 (2023) - [i110]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
SkillQG: Learning to Generate Question for Reading Comprehension Assessment. CoRR abs/2305.04737 (2023) - [i109]Tong Ye, Lingfei Wu, Tengfei Ma, Xuhong Zhang, Yangkai Du, Peiyu Liu, Wenhai Wang, Shouling Ji:
Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization. CoRR abs/2305.11074 (2023) - [i108]Gangyi Zhang, Chongming Gao, Wenqiang Lei, Xiaojie Guo, Shijun Li, Lingfei Wu, Hongshen Chen, Zhuozhi Ding, Sulong Xu, Xiangnan He:
Embracing Uncertainty: Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation. CoRR abs/2306.04487 (2023) - 2022
- [j14]Yiling Lin, James A. Evans, Lingfei Wu:
New directions in science emerge from disconnection and discord. J. Informetrics 16(1): 101234 (2022) - [j13]Lingfei Wu, Aniket Kittur, Hyejin Youn, Stasa Milojevic, Erin Leahey, Stephen M. Fiore, Yong-Yeol Ahn:
Metrics and mechanisms: Measuring the unmeasurable in the science of science. J. Informetrics 16(2): 101290 (2022) - [j12]Yutong Qu, Wei Emma Zhang, Jian Yang, Lingfei Wu, Jia Wu:
Knowledge-aware document summarization: A survey of knowledge, embedding methods and architectures. Knowl. Based Syst. 257: 109882 (2022) - [j11]Hanlu Wu, Tengfei Ma, Lingfei Wu, Fangli Xu, Shouling Ji:
Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing. ACM Trans. Knowl. Discov. Data 16(2): 27:1-27:18 (2022) - [j10]April Yi Wang, Dakuo Wang, Jaimie Drozdal, Michael J. Muller, Soya Park, Justin D. Weisz, Xuye Liu, Lingfei Wu, Casey Dugan:
Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks. ACM Trans. Comput. Hum. Interact. 29(2): 17:1-17:33 (2022) - [c81]Xiaojie Guo, Shugen Wang, Hanqing Zhao, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Jianchao Lu, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Intelligent Online Selling Point Extraction for E-commerce Recommendation. AAAI 2022: 12360-12368 - [c80]Xueying Zhang, Yanyan Zou, Hainan Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Automatic Product Copywriting for E-commerce. AAAI 2022: 12423-12431 - [c79]Xiaoqiang Wang, Bang Liu, Fangli Xu, Bo Long, Siliang Tang, Lingfei Wu:
Feeding What You Need by Understanding What You Learned. ACL (1) 2022: 5858-5874 - [c78]Linsey Pang, Wei Liu, Lingfei Wu, Kexin Xie, Stephen Guo, Raghav Chalapathy, Musen Wen:
Applied Machine Learning Methods for Time Series Forecasting. CIKM 2022: 5175-5176 - [c77]Ziyang Liu, Chaokun Wang, Hao Feng, Lingfei Wu, Liqun Yang:
Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search. EMNLP (Industry Track) 2022: 63-76 - [c76]Peng Lin, Yanyan Zou, Lingfei Wu, Mian Ma, Zhuoye Ding, Bo Long:
Automatic Scene-based Topic Channel Construction System for E-Commerce. EMNLP (Industry Track) 2022: 272-284 - [c75]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
QRelScore: Better Evaluating Generated Questions with Deeper Understanding of Context-aware Relevance. EMNLP 2022: 562-581 - [c74]Dong Chen, Lingfei Wu, Siliang Tang, Xiao Yun, Bo Long, Yueting Zhuang:
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile. ICML 2022: 3662-3678 - [c73]Jiayin Jin, Zeru Zhang, Yang Zhou, Lingfei Wu:
Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing. ICML 2022: 10340-10361 - [c72]Hanning Gao, Lingfei Wu, Po Hu, Zhihua Wei, Fangli Xu, Bo Long:
Graph-augmented Learning to Rank for Querying Large-scale Knowledge Graph. AACL/IJCNLP (1) 2022: 82-92 - [c71]Xiang Ling, Lingfei Wu, Wei Deng, Zhenqing Qu, Jiangyu Zhang, Sheng Zhang, Tengfei Ma, Bin Wang, Chunming Wu, Shouling Ji:
MalGraph: Hierarchical Graph Neural Networks for Robust Windows Malware Detection. INFOCOM 2022: 1998-2007 - [c70]Xiaochuan Fan, Chi Zhang, Yong Yang, Yue Shang, Xueying Zhang, Zhen He, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Generation of Product-Image Sequence in E-commerce. KDD 2022: 2851-2859 - [c69]Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Controllable Product Copywriting for E-Commerce. KDD 2022: 2946-2956 - [c68]Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo:
Graph Neural Networks: Foundation, Frontiers and Applications. KDD 2022: 4840-4841 - [c67]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2022). KDD 2022: 4906-4907 - [c66]Yitong Pang, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long, Jian Pei:
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation. WSDM 2022: 775-783 - [c65]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [c64]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. WWW 2022: 1601-1610 - [c63]Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, Fangli Xu, Bo Long, Jian Pei:
Multiple Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation. WWW 2022: 2153-2162 - [e1]Shusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan:
IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022. IEEE 2022, ISBN 978-1-6654-8045-1 [contents] - [i107]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. CoRR abs/2201.05540 (2022) - [i106]Fengli Xu, Lingfei Wu, James A. Evans:
Flat Teams Drive Scientific Innovation. CoRR abs/2201.06726 (2022) - [i105]Dadong Miao, Yanan Wang, Guoyu Tang, Lin Liu, Sulong Xu, Bo Long, Yun Xiao, Lingfei Wu, Yunjiang Jiang:
Sequential Search with Off-Policy Reinforcement Learning. CoRR abs/2202.00245 (2022) - [i104]Haochuan Cui, Lingfei Wu, James A. Evans:
Aging Scientists and Slowed Advance. CoRR abs/2202.04044 (2022) - [i103]Xiaoqiang Wang, Bang Liu, Fangli Xu, Bo Long, Siliang Tang, Lingfei Wu:
Feeding What You Need by Understanding What You Learned. CoRR abs/2203.02753 (2022) - [i102]Yutong Qu, Wei Emma Zhang, Jian Yang, Lingfei Wu, Jia Wu, Xindong Wu:
Embedding Knowledge for Document Summarization: A Survey. CoRR abs/2204.11190 (2022) - [i101]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
QRelScore: Better Evaluating Generated Questions with Deeper Understanding of Context-aware Relevance. CoRR abs/2204.13921 (2022) - [i100]Di Jin, Cuiying Huo, Jianwu Dang, Peican Zhu, Weixiong Zhang, Witold Pedrycz, Lingfei Wu:
Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning. CoRR abs/2205.00256 (2022) - [i99]Yangkai Du, Tengfei Ma, Lingfei Wu, Yiming Wu, Xuhong Zhang, Bo Long, Shouling Ji:
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning. CoRR abs/2205.10511 (2022) - [i98]Xueying Zhang, Kai Shen, Chi Zhang, Xiaochuan Fan, Yun Xiao, Zhen He, Bo Long, Lingfei Wu:
Scenario-based Multi-product Advertising Copywriting Generation for E-Commerce. CoRR abs/2205.10530 (2022) - [i97]Zhendong Chu, Hongning Wang, Yun Xiao, Bo Long, Lingfei Wu:
Meta Policy Learning for Cold-Start Conversational Recommendation. CoRR abs/2205.11788 (2022) - [i96]Cuiying Huo, Di Jin, Chundong Liang, Dongxiao He, Tie Qiu, Lingfei Wu:
TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature. CoRR abs/2205.12784 (2022) - [i95]Yiling Lin, Carl Benedikt Frey, Lingfei Wu:
Remote Collaboration Fuses Fewer Breakthrough Ideas. CoRR abs/2206.01878 (2022) - [i94]Dong Chen, Lingfei Wu, Siliang Tang, Xiao Yun, Bo Long, Yueting Zhuang:
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile. CoRR abs/2206.01944 (2022) - [i93]Zhizhi Yu, Di Jin, Jianguo Wei, Ziyang Liu, Yue Shang, Yun Xiao, Jiawei Han, Lingfei Wu:
TeKo: Text-Rich Graph Neural Networks with External Knowledge. CoRR abs/2206.07253 (2022) - [i92]Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Controllable Product Copywriting for E-Commerce. CoRR abs/2206.10103 (2022) - [i91]Jiayin Jin, Zeru Zhang, Yang Zhou, Lingfei Wu:
Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing. CoRR abs/2206.11423 (2022) - [i90]Xiaochuan Fan, Chi Zhang, Yong Yang, Yue Shang, Xueying Zhang, Zhen He, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Generation of Product-Image Sequence in E-commerce. CoRR abs/2206.12994 (2022) - [i89]Ziyang Liu, Chaokun Wang, Hao Feng, Lingfei Wu, Liqun Yang:
Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search. CoRR abs/2210.01701 (2022) - [i88]Peng Lin, Yanyan Zou, Lingfei Wu, Mian Ma, Zhuoye Ding, Bo Long:
Automatic Scene-based Topic Channel Construction System for E-Commerce. CoRR abs/2210.02643 (2022) - [i87]Fengli Xu, Lingfei Wu, James A. Evans:
Quantifying hierarchy in scientific teams. CoRR abs/2210.05852 (2022) - [i86]Jiajia Li, Feng Tan, Cheng He, Zikai Wang, Haitao Song, Lingfei Wu, Pengwei Hu:
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOps. CoRR abs/2211.07642 (2022) - [i85]Dongjie Wang, Lingfei Wu, Denghui Zhang, Jingbo Zhou, Leilei Sun, Yanjie Fu:
Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning. CoRR abs/2212.00904 (2022) - [i84]Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu:
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation. CoRR abs/2212.12738 (2022) - 2021
- [j9]Xiang Ling, Lingfei Wu, Saizhuo Wang, Gaoning Pan, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, Shouling Ji:
Deep Graph Matching and Searching for Semantic Code Retrieval. ACM Trans. Knowl. Discov. Data 15(5): 88:1-88:21 (2021) - [j8]Qingzhe Li, Amir Alipour-Fanid, Martin Slawski, Yanfang Ye, Lingfei Wu, Kai Zeng, Liang Zhao:
Large-scale Cost-Aware Classification Using Feature Computational Dependency Graph. IEEE Trans. Knowl. Data Eng. 33(5): 2029-2044 (2021) - [c62]Xiao Qin, Nasrullah Sheikh, Berthold Reinwald, Lingfei Wu:
Relation-aware Graph Attention Model with Adaptive Self-adversarial Training. AAAI 2021: 9368-9376 - [c61]Dadong Miao, Yanan Wang, Guoyu Tang, Lin Liu, Sulong Xu, Bo Long, Yun Xiao, Lingfei Wu, Yunjiang Jiang:
Sequential Search with Off-Policy Reinforcement Learning. CIKM 2021: 4006-4015 - [c60]Yangkai Du, Tengfei Ma, Lingfei Wu, Fangli Xu, Xuhong Zhang, Bo Long, Shouling Ji:
Constructing contrastive samples via summarization for text classification with limited annotations. EMNLP (Findings) 2021: 1365-1376 - [c59]Xuye Liu, Dakuo Wang, April Yi Wang, Yufang Hou, Lingfei Wu:
HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks. EMNLP (Findings) 2021: 4473-4485 - [c58]Zeru Zhang, Zijie Zhang, Yang Zhou, Lingfei Wu, Sixing Wu, Xiaoying Han, Dejing Dou, Tianshi Che, Da Yan:
Adversarial Attack against Cross-lingual Knowledge Graph Alignment. EMNLP (1) 2021: 5320-5337 - [c57]Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji, Kathleen R. McKeown:
Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport. EMNLP (1) 2021: 6443-6456 - [c56]Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan:
Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks. ICML 2021: 12719-12735 - [c55]April Yi Wang, Dakuo Wang, Xuye Liu, Lingfei Wu:
Graph-Augmented Code Summarization in Computational Notebooks. IJCAI 2021: 5020-5023 - [c54]Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. KDD 2021: 1161-1169 - [c53]Lingfei Wu, Yu Chen, Heng Ji, Bang Liu:
Deep Learning on Graphs for Natural Language Processing. KDD 2021: 4084-4085 - [c52]Lingfei Wu, Jiliang Tang, Yinglong Xia, Jian Pei, Xiaojie Guo:
The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21). KDD 2021: 4167-4168 - [c51]Jianpeng Xu, Lingfei Wu, Xiaolin Pang, Mohit Sharma, Dawei Yin, George Karypis, Justin Basilico, Philip S. Yu:
2nd International Workshop on Industrial Recommendation Systems (IRS). KDD 2021: 4173-4174 - [c50]Shiwei Wu, Joya Chen, Tong Xu, Liyi Chen, Lingfei Wu, Yao Hu, Enhong Chen:
Linking the Characters: Video-oriented Social Graph Generation via Hierarchical-cumulative GCN. ACM Multimedia 2021: 4716-4724 - [c49]Wenhao Yu, Lingfei Wu, Yu Deng, Qingkai Zeng, Ruchi Mahindru, Sinem Güven, Meng Jiang:
Technical Question Answering across Tasks and Domains. NAACL-HLT (Industry Papers) 2021: 178-186 - [c48]Kai Shen, Lingfei Wu, Siliang Tang, Yueting Zhuang, Zhen He, Zhuoye Ding, Yun Xiao, Bo Long:
Learning to Generate Visual Questions with Noisy Supervision. NeurIPS 2021: 11604-11617 - [c47]Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou:
Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory. NeurIPS 2021: 30196-30210 - [c46]Lingfei Wu, Yu Chen, Heng Ji, Bang Liu:
Deep Learning on Graphs for Natural Language Processing. SIGIR 2021: 2651-2653 - [c45]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. SANER 2021: 60-71 - [c44]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. SANER 2021: 330-341 - [i83]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. CoRR abs/2101.02742 (2021) - [i82]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. CoRR abs/2101.03999 (2021) - [i81]Di Tong, Lingfei Wu, James Allen Evans:
Low-skilled Occupations Face the Highest Re-skilling Pressure. CoRR abs/2101.11505 (2021) - [i80]Xiao Qin, Nasrullah Sheikh, Berthold Reinwald, Lingfei Wu:
Relation-aware Graph Attention Model With Adaptive Self-adversarial Training. CoRR abs/2102.07186 (2021) - [i79]April Yi Wang, Dakuo Wang, Jaimie Drozdal, Michael J. Muller, Soya Park, Justin D. Weisz, Xuye Liu, Lingfei Wu, Casey Dugan:
Themisto: Towards Automated Documentation Generation in Computational Notebooks. CoRR abs/2102.12592 (2021) - [i78]Yiling Lin, James Allen Evans, Lingfei Wu:
Novelty, Disruption, and the Evolution of Scientific Impact. CoRR abs/2103.03398 (2021) - [i77]Xuye Liu, Dakuo Wang, April Yi Wang, Lingfei Wu:
HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks. CoRR abs/2104.01002 (2021) - [i76]Yangkai Du, Tengfei Ma, Lingfei Wu, Fangli Xu, Xuhong Zhang, Shouling Ji:
Constructing Contrastive samples via Summarization for Text Classification with limited annotations. CoRR abs/2104.05094 (2021) - [i75]Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long:
Graph Neural Networks for Natural Language Processing: A Survey. CoRR abs/2106.06090 (2021) - [i74]Yitong Pang, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long:
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation. CoRR abs/2107.03813 (2021) - [i73]Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu C. Aggarwal, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks. CoRR abs/2107.10234 (2021) - [i72]Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long:
Graph Learning Augmented Heterogeneous Graph Neural Network for Social Recommendation. CoRR abs/2109.11898 (2021) - [i71]Qi Shen, Lingfei Wu, Yitong Pang, Yiming Zhang, Zhihua Wei, Fangli Xu, Bo Long:
Multi-behavior Graph Contextual Aware Network for Session-based Recommendation. CoRR abs/2109.11903 (2021) - [i70]Lingfei Wu, Aniket Kittur, Hyejin Youn, Stasa Milojevic, Erin Leahey, Stephen M. Fiore, Yong-Yeol Ahn:
Metrics and Mechanisms: Measuring the Unmeasurable in the Science of Science. CoRR abs/2111.07250 (2021) - [i69]Hanning Gao, Lingfei Wu, Po Hu, Zhihua Wei, Fangli Xu, Bo Long:
Graph-augmented Learning to Rank for Querying Large-scale Knowledge Graph. CoRR abs/2111.10541 (2021) - [i68]